AMD reached their goal of delivering the feature-packed ROCm 2.0 in 2018. Yesterday I covered the primary highlights on this big Radeon Open Compute stack update when there were signs of ROCm 2.0 being prepared for release this week. That milestone has now been officially released with ROCm 2.0 now being available, including the RHEL/CentOS and Ubuntu ROCm 2.0 binaries for easy installation.

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New features and enhancements in ROCm 2.0
Adds support for RHEL 7.6 / CentOS 7.6 and Ubuntu 18.04.1
Adds support for Vega 7nm
Introduces MIVisionX
A comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.
Improvements to ROCm Libraries
rocSPARSE & hipSPARSE
rocBLAS with improved DGEMM efficiency on Vega 7nm
MIOpen
This release contains general bug fixes and an updated performance database
Group convolutions backwards weights performance has been improved
RNNs now support fp16
Tensorflow multi-gpu and Tensorflow FP16 support for Vega 7nm
TensorFlow v1.12 is enabled with fp16 support
PyTorch/Caffe2 with Vega 7nm Support
fp16 support is enabled
Several bug fixes and performance enhancements
Known Issue: breaking changes are introduced in ROCm 2.0 which are not addressed upstream yet. Meanwhile, please continue to use ROCm fork at https://github.com/ROCmSoftwarePlatform/pytorch
Improvements to ROCProfiler tool
Support for Vega 7nm
Support for hipStreamCreateWithPriority
Creates a stream with the specified priority. It creates a stream on which enqueued kernels have a different priority for execution compared to kernels enqueued on normal priority streams. The priority could be higher or lower than normal priority streams.
OpenCL 2.0 support
ROCm 2.0 introduces full support for kernels written in the OpenCL 2.0 C language on certain devices and systems. Applications can detect this support by calling the “clGetDeviceInfo” query function with “parame_name” argument set to “CL_DEVICE_OPENCL_C_VERSION”. In order to make use of OpenCL 2.0 C language features, the application must include the option “-cl-std=CL2.0” in options passed to the runtime API calls responsible for compiling or building device programs. The complete specification for the OpenCL 2.0 C language can be obtained using the following link: https://www.khronos.org/registry/Ope....0-openclc.pdf
Improved Virtual Addressing (48 bit VA) management for Vega 10 and later GPUs
Fixes Clang AddressSanitizer and potentially other 3rd-party memory debugging tools with ROCm
Small performance improvement on workloads that do a lot of memory management
Removes virtual address space limitations on systems with more VRAM than system memory
Kubernetes support

Farewel happy Fields; Where Joy for ever dwells; Hail horrours, hail; Infernal world, and thou profoundest Hell; Receive thy new Possessor; One who brings; A mind not to be chang'd by Place or Time; The mind is its own place, and in it self; Can make a Heav'n of Hell, a Hell of Heav'n.

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